This invention relates to a method for entropy-based determination of object edge curves in a recorded image of a multispectral camera.
It is known that the average information content of an image is characterized by entropy. The entropy value provides information about the minimum number of bits required to store the pixels of an image. This value also provides information about whether a reduction in the required storage space can be achieved without any loss of information.
From the article by A. Shiozaki: “Edge Extraction Using Entropy Operator”; Academic Press Inc. 1986; Computer Vision, Graphics, and Image Processing, 1986, vol. 36, pages 1-9, it is known that entropy operators may be used for object edge detection in images.
Methods which utilize entropy in image processing of images recorded by air-to-surface means are known from the state of the art; edge trackers are one example. With an edge tracker, the image to be sought is examined for parallel edges. The search is terminated when the edge strength drops below a preselectable threshold. With this method it is possible to detect streets and roads. The disadvantage of this method is that it yields good results only with such objects that have a fixedly outlined object contour.
The problem addressed by the present invention is to provide a method for determining object edge curves.
This problem is solved with the features claimed. Advantageous embodiments are also claimed.
According to the invention, a method for detection and classification of objects in a recorded image includes converting the image recorded into a false color image, assigning a hue value from the HSV color space to each pixel in the false color image, such that the hue value corresponds to a hue angle H on a predetermined color circle, and classifying each pixel as one of an object pixel and background pixel, such that the pixels whose hue values are within a predetermined value range are defined as the object pixels. An entropy profile (FIG. 5) is determined by way of a displaceable evaluation window, such that the entropy of mixing S is calculated for each pixel in the recorded image from the object pixels and background pixels according to the equation
  S  =      -          k      ⁡              (                                            n              A                        ⁢            ln            ⁢                                          n                A                                                              n                  A                                +                                  n                  B                                                              +                                    n              B                        ⁢            ln            ⁢                                          n                B                                                              n                  A                                +                                  n                  B                                                                    )                            where nA denotes the number of object pixels within the evaluation window, nB denotes the number of background pixels within the evaluation window and k is a proportionality factor, anddifferentiation and extreme value consideration of the entropy profile determined is performed.        
In processing images recorded by air-to-surface means, a distinction is made between artificial and natural objects. Monochromatic objects can be defined by assigning a certain hue to them. Polychromatic objects can be defined as the sum of multiple monochromatic objects. The method according to the invention can be used in classification of monochromatic objects, i.e., those of a single color, as well as polychromatic objects, i.e., those of multiple colors.
The starting image material in modern multispectral cameras is in the form of RGB images (RGB=red, green, blue). In addition many cameras also have one more color available, which is in the infrared spectrum and is referred to as IR. Since the true color has little informational value because of what is known as color mix-up (a painted green automobile could not be differentiated from a green field on which it is parked) it must be transformed to another color space to enable this differentiation, i.e., the so-called HSV space (HSV=hue (color), S=saturation, V=volume (brightness)). There are several different methods with which those skilled in the art are familiar for this conversion, but the results are equivalent.
Invariance of the hue with respect to fluctuations in brightness forms an important difference between the representation of color and hue; whereas the color color changes because of changes in lighting conditions, the hue remains unchanged over a wide range, so that an object can be located again on the basis of the hue (H), even after a certain period of time has elapsed.